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<title>OpenCV: cv::xphoto::LearningBasedWB Class Reference</title>
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<li class="navelem"><a class="el" href="../../d2/d75/namespacecv.html">cv</a></li><li class="navelem"><a class="el" href="../../df/db9/namespacecv_1_1xphoto.html">xphoto</a></li><li class="navelem"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html">LearningBasedWB</a></li>  </ul>
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<a href="#pub-methods">Public Member Functions</a> |
<a href="../../da/d7c/classcv_1_1xphoto_1_1LearningBasedWB-members.html">List of all members</a>  </div>
  <div class="headertitle">
<div class="title">cv::xphoto::LearningBasedWB Class Reference<span class="mlabels"><span class="mlabel">abstract</span></span><div class="ingroups"><a class="el" href="../../de/daa/group__xphoto.html">Additional photo processing algorithms</a></div></div>  </div>
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<p>More sophisticated learning-based automatic white balance algorithm.  
 <a href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#details">More...</a></p>
<p><code>#include &lt;opencv2/xphoto/white_balance.hpp&gt;</code></p>
<div class="dynheader">
Inheritance diagram for cv::xphoto::LearningBasedWB:</div>
<div class="dyncontent">
 <div class="center">
  <img alt="" src="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.png" usemap="#cv::xphoto::LearningBasedWB_map"/>
  <map id="cv::xphoto::LearningBasedWB_map" name="cv::xphoto::LearningBasedWB_map">
<area alt="cv::xphoto::WhiteBalancer" coords="0,56,179,80" href="../../d9/d7a/classcv_1_1xphoto_1_1WhiteBalancer.html" shape="rect" title="The base class for auto white balance algorithms. "/>
<area alt="cv::Algorithm" coords="0,0,179,24" href="../../d3/d46/classcv_1_1Algorithm.html" shape="rect" title="This is a base class for all more or less complex algorithms in OpenCV. "/>
</map>
 </div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:aeeaca052262a01d0feed6312ccb9a76e"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#aeeaca052262a01d0feed6312ccb9a76e">extractSimpleFeatures</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> src, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst)=0</td></tr>
<tr class="memdesc:aeeaca052262a01d0feed6312ccb9a76e"><td class="mdescLeft"> </td><td class="mdescRight">Implements the feature extraction part of the algorithm.  <a href="#aeeaca052262a01d0feed6312ccb9a76e">More...</a><br/></td></tr>
<tr class="separator:aeeaca052262a01d0feed6312ccb9a76e"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:abfe7d3983f8245a7eba0a7f9de40e3e1"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#abfe7d3983f8245a7eba0a7f9de40e3e1">getHistBinNum</a> () const =0</td></tr>
<tr class="memdesc:abfe7d3983f8245a7eba0a7f9de40e3e1"><td class="mdescLeft"> </td><td class="mdescRight">Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image).  <a href="#abfe7d3983f8245a7eba0a7f9de40e3e1">More...</a><br/></td></tr>
<tr class="separator:abfe7d3983f8245a7eba0a7f9de40e3e1"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a764b51265b5a1bd7bd11ce9d14d6f75f"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a764b51265b5a1bd7bd11ce9d14d6f75f">getRangeMaxVal</a> () const =0</td></tr>
<tr class="memdesc:a764b51265b5a1bd7bd11ce9d14d6f75f"><td class="mdescLeft"> </td><td class="mdescRight">Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images)  <a href="#a764b51265b5a1bd7bd11ce9d14d6f75f">More...</a><br/></td></tr>
<tr class="separator:a764b51265b5a1bd7bd11ce9d14d6f75f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ae7eb310249709c2aef41d6399ebd7660"><td align="right" class="memItemLeft" valign="top">virtual float </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#ae7eb310249709c2aef41d6399ebd7660">getSaturationThreshold</a> () const =0</td></tr>
<tr class="memdesc:ae7eb310249709c2aef41d6399ebd7660"><td class="mdescLeft"> </td><td class="mdescRight">Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds \(\texttt{saturation_threshold}\times\texttt{range_max_val}\) are ignored.  <a href="#ae7eb310249709c2aef41d6399ebd7660">More...</a><br/></td></tr>
<tr class="separator:ae7eb310249709c2aef41d6399ebd7660"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a3381bd425bc4201133c9669071908e7f"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a3381bd425bc4201133c9669071908e7f">setHistBinNum</a> (int val)=0</td></tr>
<tr class="memdesc:a3381bd425bc4201133c9669071908e7f"><td class="mdescLeft"> </td><td class="mdescRight">Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image).  <a href="#a3381bd425bc4201133c9669071908e7f">More...</a><br/></td></tr>
<tr class="separator:a3381bd425bc4201133c9669071908e7f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a3d9395274be8053b2f09e46d11a24a65"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a3d9395274be8053b2f09e46d11a24a65">setRangeMaxVal</a> (int val)=0</td></tr>
<tr class="memdesc:a3d9395274be8053b2f09e46d11a24a65"><td class="mdescLeft"> </td><td class="mdescRight">Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images)  <a href="#a3d9395274be8053b2f09e46d11a24a65">More...</a><br/></td></tr>
<tr class="separator:a3d9395274be8053b2f09e46d11a24a65"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a9bff5a507d4dffc58e16d85b1d07f35f"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a9bff5a507d4dffc58e16d85b1d07f35f">setSaturationThreshold</a> (float val)=0</td></tr>
<tr class="memdesc:a9bff5a507d4dffc58e16d85b1d07f35f"><td class="mdescLeft"> </td><td class="mdescRight">Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds \(\texttt{saturation_threshold}\times\texttt{range_max_val}\) are ignored.  <a href="#a9bff5a507d4dffc58e16d85b1d07f35f">More...</a><br/></td></tr>
<tr class="separator:a9bff5a507d4dffc58e16d85b1d07f35f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_methods_classcv_1_1xphoto_1_1WhiteBalancer"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classcv_1_1xphoto_1_1WhiteBalancer')"><img alt="-" src="../../closed.png"/> Public Member Functions inherited from <a class="el" href="../../d9/d7a/classcv_1_1xphoto_1_1WhiteBalancer.html">cv::xphoto::WhiteBalancer</a></td></tr>
<tr class="memitem:ae23838a1a54f101b255bca1a97418aa3 inherit pub_methods_classcv_1_1xphoto_1_1WhiteBalancer"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d7a/classcv_1_1xphoto_1_1WhiteBalancer.html#ae23838a1a54f101b255bca1a97418aa3">balanceWhite</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> src, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst)=0</td></tr>
<tr class="memdesc:ae23838a1a54f101b255bca1a97418aa3 inherit pub_methods_classcv_1_1xphoto_1_1WhiteBalancer"><td class="mdescLeft"> </td><td class="mdescRight">Applies white balancing to the input image.  <a href="../../d9/d7a/classcv_1_1xphoto_1_1WhiteBalancer.html#ae23838a1a54f101b255bca1a97418aa3">More...</a><br/></td></tr>
<tr class="separator:ae23838a1a54f101b255bca1a97418aa3 inherit pub_methods_classcv_1_1xphoto_1_1WhiteBalancer"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Public Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a827c8b2781ed17574805f373e6054ff1 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a827c8b2781ed17574805f373e6054ff1">Algorithm</a> ()</td></tr>
<tr class="separator:a827c8b2781ed17574805f373e6054ff1 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a8ae826127fa0f1f8d10a24841bd376f8 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a8ae826127fa0f1f8d10a24841bd376f8">~Algorithm</a> ()</td></tr>
<tr class="separator:a8ae826127fa0f1f8d10a24841bd376f8 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#aec9c965448e4dc851d7cacd3abd84cd1">clear</a> ()</td></tr>
<tr class="memdesc:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Clears the algorithm state.  <a href="../../d3/d46/classcv_1_1Algorithm.html#aec9c965448e4dc851d7cacd3abd84cd1">More...</a><br/></td></tr>
<tr class="separator:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab6a18f1825475643e94381697d413972 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#ab6a18f1825475643e94381697d413972">empty</a> () const</td></tr>
<tr class="memdesc:ab6a18f1825475643e94381697d413972 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Returns true if the <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html" title="This is a base class for all more or less complex algorithms in OpenCV. ">Algorithm</a> is empty (e.g. in the very beginning or after unsuccessful read.  <a href="../../d3/d46/classcv_1_1Algorithm.html#ab6a18f1825475643e94381697d413972">More...</a><br/></td></tr>
<tr class="separator:ab6a18f1825475643e94381697d413972 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a286fc82744ccab3d248aca44524266a9 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a286fc82744ccab3d248aca44524266a9">getDefaultName</a> () const</td></tr>
<tr class="separator:a286fc82744ccab3d248aca44524266a9 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#aef2ad3f4145bd6e8c3664eb1c4b5e1e6">read</a> (const <a class="el" href="../../de/dd9/classcv_1_1FileNode.html">FileNode</a> &amp;fn)</td></tr>
<tr class="memdesc:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Reads algorithm parameters from a file storage.  <a href="../../d3/d46/classcv_1_1Algorithm.html#aef2ad3f4145bd6e8c3664eb1c4b5e1e6">More...</a><br/></td></tr>
<tr class="separator:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a0a880744bc4e3f45711444571df47d67 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a0a880744bc4e3f45711444571df47d67">save</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filename) const</td></tr>
<tr class="separator:a0a880744bc4e3f45711444571df47d67 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1f8ad7b8add515077367fb9949a174d2 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a1f8ad7b8add515077367fb9949a174d2">write</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp;fs) const</td></tr>
<tr class="memdesc:a1f8ad7b8add515077367fb9949a174d2 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Stores algorithm parameters in a file storage.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a1f8ad7b8add515077367fb9949a174d2">More...</a><br/></td></tr>
<tr class="separator:a1f8ad7b8add515077367fb9949a174d2 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a763a62d1b03042eef7d7fc3ac6c87c79">write</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &gt; &amp;fs, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;name=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>()) const</td></tr>
<tr class="memdesc:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a763a62d1b03042eef7d7fc3ac6c87c79">More...</a><br/></td></tr>
<tr class="separator:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
Additional Inherited Members</h2></td></tr>
<tr class="inherit_header pub_static_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Static Public Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b">load</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filename, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;objname=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Loads algorithm from the file.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b">More...</a><br/></td></tr>
<tr class="separator:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a3ba305a10d02479c13cf7d169c321547">loadFromString</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;strModel, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;objname=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Loads algorithm from a String.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a3ba305a10d02479c13cf7d169c321547">More...</a><br/></td></tr>
<tr class="separator:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#ad8c591bacb34c485f5b7a250c314fc53">read</a> (const <a class="el" href="../../de/dd9/classcv_1_1FileNode.html">FileNode</a> &amp;fn)</td></tr>
<tr class="memdesc:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Reads algorithm from the file node.  <a href="../../d3/d46/classcv_1_1Algorithm.html#ad8c591bacb34c485f5b7a250c314fc53">More...</a><br/></td></tr>
<tr class="separator:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pro_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Protected Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a68eeca71617474ad3d4561786f0289d2 inherit pro_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a68eeca71617474ad3d4561786f0289d2">writeFormat</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp;fs) const</td></tr>
<tr class="separator:a68eeca71617474ad3d4561786f0289d2 inherit pro_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<a id="details" name="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>More sophisticated learning-based automatic white balance algorithm. </p>
<p>As <a class="el" href="../../d7/d71/classcv_1_1xphoto_1_1GrayworldWB.html">GrayworldWB</a>, this algorithm works by applying different gains to the input image channels, but their computation is a bit more involved compared to the simple gray-world assumption. More details about the algorithm can be found in <a class="el" href="../../d0/de3/citelist.html#CITEREF_Cheng2015">[46]</a> .</p>
<p>To mask out saturated pixels this function uses only pixels that satisfy the following condition:</p>
<p class="formulaDsp">
\[ \frac{\textrm{max}(R,G,B)}{\texttt{range_max_val}} &lt; \texttt{saturation_thresh} \]
</p>
<p>Currently supports images of type <a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga88c4cd9de76f678f33928ef1e3f96047">CV_8UC3</a> and <a class="el" href="../../d1/d1b/group__core__hal__interface.html#gad2358c569de8fe354451244bd3c01b9b">CV_16UC3</a>. </p>
</div><h2 class="groupheader">Member Function Documentation</h2>
<a id="aeeaca052262a01d0feed6312ccb9a76e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aeeaca052262a01d0feed6312ccb9a76e">◆ </a></span>extractSimpleFeatures()</h2>
<div class="memitem">
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          <td class="memname">virtual void cv::xphoto::LearningBasedWB::extractSimpleFeatures </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>src</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.xphoto_LearningBasedWB.extractSimpleFeatures(</td><td class="paramname">src[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Implements the feature extraction part of the algorithm. </p>
<p>In accordance with <a class="el" href="../../d0/de3/citelist.html#CITEREF_Cheng2015">[46]</a> , computes the following features for the input image:</p><ol type="1">
<li>Chromaticity of an average (R,G,B) tuple</li>
<li>Chromaticity of the brightest (R,G,B) tuple (while ignoring saturated pixels)</li>
<li>Chromaticity of the dominant (R,G,B) tuple (the one that has the highest value in the RGB histogram)</li>
<li>Mode of the chromaticity palette, that is constructed by taking 300 most common colors according to the RGB histogram and projecting them on the chromaticity plane. Mode is the most high-density point of the palette, which is computed by a straightforward fixed-bandwidth kernel density estimator with a Epanechnikov kernel function.</li>
</ol>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">src</td><td>Input three-channel image (BGR color space is assumed). </td></tr>
    <tr><td class="paramname">dst</td><td>An array of four (r,g) chromaticity tuples corresponding to the features listed above. </td></tr>
  </table>
  </dd>
</dl>
</div>
</div>
<a id="abfe7d3983f8245a7eba0a7f9de40e3e1"></a>
<h2 class="memtitle"><span class="permalink"><a href="#abfe7d3983f8245a7eba0a7f9de40e3e1">◆ </a></span>getHistBinNum()</h2>
<div class="memitem">
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  <td class="mlabels-left">
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          <td class="memname">virtual int cv::xphoto::LearningBasedWB::getHistBinNum </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.xphoto_LearningBasedWB.getHistBinNum(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image). </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a3381bd425bc4201133c9669071908e7f" title="Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the...">setHistBinNum</a> </dd></dl>
</div>
</div>
<a id="a764b51265b5a1bd7bd11ce9d14d6f75f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a764b51265b5a1bd7bd11ce9d14d6f75f">◆ </a></span>getRangeMaxVal()</h2>
<div class="memitem">
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  <td class="mlabels-left">
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          <td class="memname">virtual int cv::xphoto::LearningBasedWB::getRangeMaxVal </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.xphoto_LearningBasedWB.getRangeMaxVal(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images) </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a3d9395274be8053b2f09e46d11a24a65" title="Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images) ...">setRangeMaxVal</a> </dd></dl>
</div>
</div>
<a id="ae7eb310249709c2aef41d6399ebd7660"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ae7eb310249709c2aef41d6399ebd7660">◆ </a></span>getSaturationThreshold()</h2>
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          <td class="memname">virtual float cv::xphoto::LearningBasedWB::getSaturationThreshold </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.xphoto_LearningBasedWB.getSaturationThreshold(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds \(\texttt{saturation_threshold}\times\texttt{range_max_val}\) are ignored. </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a9bff5a507d4dffc58e16d85b1d07f35f" title="Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels ...">setSaturationThreshold</a> </dd></dl>
</div>
</div>
<a id="a3381bd425bc4201133c9669071908e7f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3381bd425bc4201133c9669071908e7f">◆ </a></span>setHistBinNum()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">virtual void cv::xphoto::LearningBasedWB::setHistBinNum </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.xphoto_LearningBasedWB.setHistBinNum(</td><td class="paramname">val</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image). </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#abfe7d3983f8245a7eba0a7f9de40e3e1" title="Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the...">getHistBinNum</a> </dd></dl>
</div>
</div>
<a id="a3d9395274be8053b2f09e46d11a24a65"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3d9395274be8053b2f09e46d11a24a65">◆ </a></span>setRangeMaxVal()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">virtual void cv::xphoto::LearningBasedWB::setRangeMaxVal </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.xphoto_LearningBasedWB.setRangeMaxVal(</td><td class="paramname">val</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images) </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#a764b51265b5a1bd7bd11ce9d14d6f75f" title="Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images) ...">getRangeMaxVal</a> </dd></dl>
</div>
</div>
<a id="a9bff5a507d4dffc58e16d85b1d07f35f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a9bff5a507d4dffc58e16d85b1d07f35f">◆ </a></span>setSaturationThreshold()</h2>
<div class="memitem">
<div class="memproto">
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  <tr>
  <td class="mlabels-left">
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          <td class="memname">virtual void cv::xphoto::LearningBasedWB::setSaturationThreshold </td>
          <td>(</td>
          <td class="paramtype">float </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.xphoto_LearningBasedWB.setSaturationThreshold(</td><td class="paramname">val</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds \(\texttt{saturation_threshold}\times\texttt{range_max_val}\) are ignored. </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d4/d3b/classcv_1_1xphoto_1_1LearningBasedWB.html#ae7eb310249709c2aef41d6399ebd7660" title="Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels ...">getSaturationThreshold</a> </dd></dl>
</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>opencv2/xphoto/<a class="el" href="../../d9/dcd/white__balance_8hpp.html">white_balance.hpp</a></li>
</ul>
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